Abstract

This paper derives energy-optimal batching periods
for asynchronous multistage data processing on sensor
nodes in the sense of minimizing energy consumption
while meeting end-to-end deadlines. Batching the processing
of (sensor) data maximizes processor sleep periods,
hence minimizing the wakeup frequency and the
corresponding overhead. The algorithm is evaluated on
mPlatform, a next-generation heterogeneous sensor node
platform equipped with both a low-end microcontroller
(MSP430) and a higher-end embedded systems processor
(ARM). Experimental results show that the total energy
consumption of mPlatform, when processing data flows
at their optimal batching periods, is up to 35% lower than
that for uniform period assignment. Moreover, processing
data at the appropriate processor can use as much as
80% less energy than running the same task set on the
ARM alone and 25% less energy than running the task
set on the MSP430 alone.

Details

Publication type

Proceedings

Published in

Proc. of IEEE Real Time Technology and Applications Symposium (RTAS2010)